Low-cost, low-input RNA-seq protocols perform nearly as well as high-input protocols
Ontology highlight
ABSTRACT: We sequenced mRNA according to several library prep protocols with known mixtures of two species of Drosophila in order to establish linear response in each protocol.
Project description:Recently, a number of protocols extending RNA-sequencing to the single-cell regime have been published. However, we were concerned that the additional steps to deal with such minute quantities of input sample would introduce serious biases that would make analysis of the data using existing approaches invalid. In this study, we performed a critical evaluation of several of these low-volume RNA-seq protocols, and found that they performed slightly less well in per-gene linearity of response, but with at least two orders of magnitude less sample required. We also explored a simple modification to one of these protocols that, for many samples, reduced the cost of library preparation to approximately $20/sample.
Project description:Single-cell RNA -seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA -seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We characterize Seq-Well extensively and use it to profile thousands of primary human macrophages exposed to tuberculosis.
Project description:Satellite services are fundamental to the global economy, and their design reflects a tradeoff between coverage and cost. Here, we report the discovery of two alternative 4-satellite constellations with 24- and 48-hour periods, both of which attain nearly continuous global coverage. The 4-satellite constellations harness energy from nonlinear orbital perturbation forces (e.g., Earth's geopotential, gravitational effects of the sun and moon, and solar radiation pressure) to reduce their propellant and maintenance costs. Our findings demonstrate that small sacrifices in global coverage at user-specified longitudes allow operationally viable constellations with significantly reduced mass-to-orbit costs and increased design life. The 24-hour period constellation reduces the overall required vehicle mass budget for propellant by approximately 60% compared to a geostationary Earth orbit constellation with similar coverage over typical satellite lifetimes. Mass savings of this magnitude permit the use of less expensive launch vehicles, installation of additional instruments, and substantially improved mission life.
Project description:We developed a new method on sequencing low-input RNA. This method shows much low-bias with the advantage of semiconductor while competing with smart-seq2. In order to analyze the low-input RNA datasets sensitively, we also develop FANSe2splice with high experimental verification rate as the analysis tool in our method.
Project description:We evaluated the performance of 5 library prep protocols by using total mRNA and IP RNA of mouse liver,we found all the 5 library preparation kits detect more enrichment effects than depletion effect. The profiles being generated by SMARTer kit is different than all other kits.
Project description:Low-input RNA-seq is powerful to represent the gene expression profiles with limited number of cells, especially when single-cell variations are not the aim. However, pre-amplification-based and molecule index-based library construction methods boost bias or require higher throughput. Here we demonstrate a simple, low-cost, low-bias and low-input RNA-seq with ion torrent semiconductor sequencing (LIEA RNA-seq). We also developed highly accurate and error-tolerant spliced mapping algorithm FANSe2splice to accurately map the single-ended reads to the reference genome with better experimental verifiability than the previous spliced mappers. Combining the experimental and computational advancements, our solution is comparable with the bulk mRNA-seq in quantification, reliably detects splice junctions and minimizes the bias with much less mappable reads.
Project description:RNA sequencing is a powerful approach to quantify the genome-wide distribution of mRNA molecules in a population to gain deeper understanding of cellular functions and phenotypes. However, unlike eukaryotic cells, mRNA sequencing of bacterial samples is more challenging due to the absence of a poly-A tail that typically enables efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Moreover, bacterial cells frequently contain 100-fold lower quantities of RNA compared to mammalian cells, which further complicates mRNA sequencing from non-cultivable and non-model bacterial species which are often present in low abundance. To overcome these limitations, we report EMBR-seq (Enrichment of mRNA by Blocked rRNA), a method that efficiently depletes 5S, 16S and 23S rRNA using blocking primers to prevent their amplification. EMBR-seq results in greater than 80% of the sequenced RNA molecules deriving from mRNA. We demonstrate that this increased efficiency provides a deeper view of the transcriptome without introducing technical amplification-induced biases. Moreover, compared to recent methods that employ a large array of oligonucleotides to deplete rRNA, EMBR-seq employs a single oligonucleotide per rRNA, thereby making this new technology significantly more cost-effective, especially when applied to varied bacterial species. Finally, compared to existing commercial kits, we show that EMBR-seq can be used to successfully quantify the transcriptome from more than 500-fold lower starting total RNA. Thus, EMBR-seq provides an efficient and cost-effective approach to quantify global gene expression profiles from low input bacterial samples.